Open Geospatial System for LUCAS In Situ Data Harmonization and Distribution

Abstract

The use of in situ references in Earth observation monitoring is a fundamental need. LUCAS (Land Use and Coverage Area frame Survey) is an activity which has performed repeated in situ surveys over Europe every three years since 2006. The dataset is unique in many aspects, however it is currently not available through a standardized interface, machine-to-machine. Moreover, the evolution of the surveys limits the change analysis with the dataset. Our goal was to develop an open-source system to fill these gaps. This paper presents a developed system solution for the LUCAS in situ data harmonization and distribution. We have designed a multi-layer client-server system which can be integrated into end-to-end workflows. It provides data through an OGC (Open Geospatial Consortium) compliant interface. Moreover, a geospatial user can integrate the data through a Python API (Application Programming Interface) to ease the use in the workflows with spatial, temporal, attribute, and thematic filters. On top of that, we have implemented a QGIS plugin to retrieve the spatio-temporal subsets of the data interactively. Additionally, the Python API includes methods to manage thematic information. The system provides enhanced functionality which is demonstrated in two application use cases.

Assessment of Soil Sustainability Using the LUCAS Database in the Southwest Region of Romania

“…Soil sampling and analysis results are strongly influenced by the weather conditions and the agricultural season stage. With the help of the GPS technology (photos, maps, and orthophotographs), it was possible to relocate on the field in 2007, and all the points were correctly investigated in 2006 [15,[20][21][22]29,[41][42][43][44][45]47,48,50,51].…”

“…Each point in the basic sample is photo-interpreted, and it is incorporated in one of the seven predefined land cover categories (arable land, permanent crops, permanent pastures, forestry, shrubland, empty or low/rare vegetation land, water, or artificial land). A subsample, called a field sample, shall be extracted from the basic stratified sample to be classified following the field visit according to the established nomenclature [15,[22][23][24]46,47].…”

“…Out of the 7867 points on the Romanian territory, soil samples were collected from 1614 points, and the quality physicochemical indicators were analyzed to use these results in the assessment of the quality of environmental factors, to update the European soil maps, validate soil patterns, and measure the amount of organic carbon in the soil-an important factor in climate change analysis. The study occurred in the field and was carried out in its current form every 3 years, between 2009 and 2018, and also in 2022, 4 years after the last study [15,20,26,27,[48][49][50][51].…”

“…A point has no width or length and corresponds to a circle with a radius of 1.5 m (diameter 3 m), representing an area of 7 m 2 , which falls into a homogeneous area (arable land, upper part of a house) [15,[20][21][22]44,45,50].…”

Graph Neural Network-Based Method of Spatiotemporal Land Cover Mapping Using Satellite Imagery

“…These surveys provide rich data on the LULC, and agro-environmental information for supporting spatial, territorial and agricultural analyses. To address the dataset’s limitations and to make it more accessible, an open-source system was developed to integrate the LUCAS dataset into workflows [ 25 ]. A recently released dataset named Dynamic World NRT offers a global 10 m resolution LULC map with 9 classes [ 26 ].…”